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Logistic Regression for Dependent Binary Observations
Abstract
The likelihood of a set of binary dependent outcomes, with or without explanatory variables, is expressed as a product of conditional probabilities each of which is assumed to be logistic. The models are called regressive logistic models. They provide a simple but relatively unknown parametrization of the multivariate distribution. They have the theoretical and practical advantage that they can be analyzed and fitted as in logistic regression for independent outcomes, and with the same computer programs. The paper is largely expository and is intended to motivate the development and usage of the regressive logistic models. The discussion includes serially dependent outcomes, equally predictive outcomes, more specialized patterns of dependence, multidimensional tables, and three examples.
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Social Class, Parental Encouragement, and Educational Aspirations
Sewell, W. H., & Shah, V. P. (1968) · American Journal of Sociology · doi:10.1086/224530 · Cited by 457
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Marenberg, M. E., Risch, N., Berkman, L. F., Floderus, B., & de Faire, U. (1994) · New England Journal of Medicine · doi:10.1056/nejm199404143301503 · Cited by 1,255
Analysis of frequency count data using the negative binomial distribution
White, G. C., & Bennetts, R. E. (1996) · Ecology · doi:10.2307/2265753 · Cited by 465
The role of acute and chronic stress in asthma attacks in children
Sandberg, S., Paton, J. Y., Ahola, S., McCann, D. C., McGuinness, D., Hillary, C. R., & Oja, H. (2000) · The Lancet · doi:10.1016/s0140-6736(00)02715-x · Cited by 464
Comparing compliance patterns between randomized treatments
Vrijens, B., & Goetghebeur, E. (1997) · Controlled Clinical Trials · doi:10.1016/s0197-2456(96)00235-8 · Cited by 114
Metadata
- Authors
- Bonney, G. E.
- Venue
- Biometrics
- Publisher
- JSTOR
- Published
- 1987-12
- Volume
- 43
- Issue
- 4
- Pages
- 951
- ISSN
- 0006-341X (ISSN-L)
- OpenAlex
- W2020712165
- Cited by
- 235
- References
- 1
- FWCI
- 8.52
- Type
- journal article
- Language
- en
- Open access
- closed
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- Bonney, G. E. (1987). Logistic Regression for Dependent Binary Observations. Biometrics. https://doi.org/10.2307/2531548
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